Dynamic Expert Matching via Communication Analysis
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Solution Overview
Problem
Current systems for identifying and matching expertise in call centers are inefficient due to reliance on static databases that may not capture all areas of expertise, lack of guidance for finding relevant experts, and failure to recognize professionals with expertise outside their job functions or training status.
Innovation Solution
An automated electronic communication system using expert and agent term extraction engines, coupled with a matching engine, dynamically identifies and matches expertise by analyzing electronic communications, providing real-time expert recommendations without manual input or predefined skills.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static database is used to store expert information, then the system structure is simple, but the system cannot capture all areas of expertise and fails to identify experts dynamically
Solution Approach 1:
The patent transforms the static database into a dynamic system that automatically updates expert profiles by analyzing electronic communications. The system continuously monitors communication data, extracts expertise information, and updates employee profiles in real-time, enabling the database to adapt to changing expertise areas without manual intervention.
Solution Approach 2:
The system performs self-updating by automatically analyzing electronic communications to identify and register expertise areas. The communication analysis module extracts expertise information from communication data and automatically updates the employee profiles, eliminating the need for manual expertise registration and allowing the system to serve itself in maintaining current expertise knowledge.
2Productivity
If agents manually review a directory for potential experts, then the system operation is simple, but the process is time-consuming and lacks guidance on finding relevant experts
Solution Approach 1:
The patent introduces an intermediary system consisting of the communication analysis module and expertise matching module. This intermediary automatically analyzes electronic communications, extracts expertise information, and matches it with customer inquiries, serving as a mediator between agents and experts. The system provides guided recommendations with relevance scores, making the expert search process both fast and easy to operate.
3Quantity of substance
If expertise is entered into the database manually, then the data structure is simple, but the database cannot include all areas of expertise and particular desired areas of expertise
Solution Approach 1:
The system automatically extracts expertise information from electronic communications and updates employee profiles without manual data entry. The communication analysis module processes communication data, identifies expertise areas, and automatically registers them in the database, enabling comprehensive coverage of all expertise areas including those that emerge organically from communication patterns.
Solution Approach 2:
The patent replaces the mechanical manual data entry process with an automated communication analysis system. Instead of manually entering expertise information, the system uses natural language processing and data extraction techniques to automatically identify and register expertise areas from electronic communications, significantly expanding expertise coverage.
4Adaptability or versatility
If professionals are identified as experts based on their job function, then the classification is simple, but the system cannot recognize professionals with expertise outside their normal role or area of expertise
Solution Approach 1:
The system automatically identifies expertise areas by analyzing the content of electronic communications rather than relying on predefined job functions. The communication analysis module extracts expertise information from actual communication behavior, allowing professionals to be recognized as experts in areas outside their formal job descriptions based on their actual communication patterns and knowledge demonstration.
Data Source
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AI summary
A method and system automatically matching experts with an agent request for an expert are disclosed. Exemplary systems include an expert term extraction engine to extract expert terms from communications involving experts, and an agent term extraction engine to extract an agent request from a communications involving agents, and a matching engine to compare agent request terms to the expert terms from the expert term extraction engine and to determine whether there is a match. In case of positive match the communication between the agent and a customer from which the request is extracted is connected to the corresponding expert with the matched skills.